M.h. Vahidnia, A.a. Alesheikh, A. Alimohammadi, F. Hosseinali,
Volume 7, Issue 3 (9-2009)
Abstract
Landslides are major natural hazards which not only result in the loss of human life but also cause economic
burden on the society. Therefore, it is essential to develop suitable models to evaluate the susceptibility of slope failures
and their zonations. This paper scientifically assesses various methods of landslide susceptibility zonation in GIS
environment. A comparative study of Weights of Evidence (WOE), Analytical Hierarchy Process (AHP), Artificial
Neural Network (ANN), and Generalized Linear Regression (GLR) procedures for landslide susceptibility zonation is
presented. Controlling factors such as lithology, landuse, slope angle, slope aspect, curvature, distance to fault, and
distance to drainage were considered as explanatory variables. Data of 151 sample points of observed landslides in
Mazandaran Province, Iran, were used to train and test the approaches. Small scale maps (1:1,000,000) were used in
this study. The estimated accuracy ranges from 80 to 88 percent. It is then inferred that the application of WOE in
rating maps’ categories and ANN to weight effective factors result in the maximum accuracy.
Fabrizio Palmisano, Angelo Elia,
Volume 12, Issue 2 (6-2014)
Abstract
The increase in the computational capabilities in the last decade has allowed numerical models to be widely used in the analysis, leading to a higher complexity in structural engineering. This is why simple models are nowadays essential because they provide easy and accessible understanding of fundamental aspects of the structural response. Accordingly, this article aims at showing the utility and effectiveness of a simple method (i.e. the Load Path Method) in the interpretation of the behaviour of masonry buildings subjected to foundation settlements due to landslide. Models useful for understanding brick-mortar interface behaviour as well as the global one are reported. The global proposed approach is also validated by using Bi-directional Evolutionary Structural Optimization method.
Moreover, drawing inspiration from a case study, the article shows that the proposed approach is useful for the diagnosis of crack patterns of masonry structures subjected to landslide movements.